On the use of Jacobian adaptation in real speaker verification applications

Jacobian Adaptation (JA) of the acoustic models is a fast adaptation technique that has been successfully used in both speech and speaker recognition systems. This technique adapts the acoustic models on the basis of the difference between the testing and the training noise conditions. For this reason, a noise reference of both the training and the testing phase is needed. In previous works, the noise conditions have been commonly supposed to be known, or estimated from the first part of the signals or using manually obtained speech and non-speech labels. However, in a real application the noise conditions are not generally known, it is not sure that the first part of the signal does not contain speech and manual labels are not usually available. In this work we propose to obtain the noise references by using continuous noise estimation methods, which are more appropriate for real applications. Several noise estimation methods are compared and the obtained results show that these techniques are effective for JA.